Multi-Scenario Tube-Based Model Predictive Control for Irrigation Canals with Human Interventions

This article considers irrigation canal control problems where human agents are free to move along the canal temporarily overriding the position of actuators, which are considered to be electromechanical gates. To deal with this issue, the centralized controller is robustified against human interventions by following a tube-based model predictive control approach. To decrease conservatism, the controller considers explicitly the different scenarios for human interventions. Also, the ancillary control law implemented by the tube-based MPC controller is computed using a modular feedback gain that is designed to be resilient against the loss of control inputs. To illustrate the effectiveness of the proposed method, the American Society of Civil Engineers (ASCE) Test Canal 2 is used as a case study.